Survivorship, measured: March cohorts of US symbols still trading in late July 2026
Answered against 22 years of US equities and 12 years of US options data and published with the query that produced it. This result is stored as of 2026-08-05, from Local A-Share Data Lake for AI Agents.
| year | names_on_tape_count | still_trading_count | gone_count | still_trading_pct |
|---|---|---|---|---|
| 2016 | 8101 | 4061 | 4040 | 50.1 |
| 2017 | 8135 | 4273 | 3862 | 52.5 |
| 2018 | 8298 | 4576 | 3722 | 55.1 |
| 2019 | 8491 | 4932 | 3559 | 58.1 |
| 2020 | 8792 | 5422 | 3370 | 61.7 |
| 2021 | 9981 | 5937 | 4044 | 59.5 |
| 2022 | 11553 | 6914 | 4639 | 59.8 |
| 2023 | 11096 | 7479 | 3617 | 67.4 |
| 2024 | 10703 | 8310 | 2393 | 77.6 |
| 2025 | 11084 | 9614 | 1470 | 86.7 |
- Rows × columns
- 10 × 5
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
year |
number | 2,016 to 2,025 | |
names_on_tape_count |
number | 8,101 to 11,553 | count |
still_trading_count |
number | 4,061 to 9,614 | count |
gone_count |
number | 1,470 to 4,639 | count |
still_trading_pct |
number | 50.1 to 86.7 | percent |
Computed from Strasmore's warehouse of US exchange, SIP and OPRA market data. Equity prices are delayed; options greeks and implied volatility are end-of-day. This result is stored, not recomputed on load — it is exactly the numbers that were returned on , and the query below is what returned them.
Run it yourself
This is the exact query behind the result above. Change a ticker, a date or a column and run it against the warehouse — no account, no key. The no-signup tier is smaller than the one this page was computed on; a query that reaches past it comes back saying which plan runs it.
WITH on_tape_now AS (
SELECT ticker
FROM global_markets.delayed_stocks_minute_aggs
WHERE toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2026-07-20')
AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-07-31')
GROUP BY ticker
),
cohort AS (
SELECT toYear(toTimeZone(window_start, 'America/New_York')) AS cohort_year,
ticker
FROM global_markets.delayed_stocks_minute_aggs
WHERE toYear(toTimeZone(window_start, 'America/New_York')) BETWEEN 2016 AND 2025
AND toMonth(toTimeZone(window_start, 'America/New_York')) = 3
AND toDayOfMonth(toTimeZone(window_start, 'America/New_York')) BETWEEN 10 AND 14
GROUP BY cohort_year, ticker
)
SELECT c.cohort_year AS year,
count() AS names_on_tape_count,
countIf(n.ticker != '') AS still_trading_count,
count() - countIf(n.ticker != '') AS gone_count,
round(100 * countIf(n.ticker != '') / count(), 1) AS still_trading_pct
FROM cohort AS c
LEFT JOIN on_tape_now AS n ON c.ticker = n.ticker
GROUP BY year
ORDER BY year
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